研究数据普通数据

面板数据熵值法综合评价Stata案例

数据格式 Stata / Stata代码 / PDF / Word更新日期

数据摘要

多指标综合评价需要明确标准化与赋权步骤。本资料提供面板数据熵值法Stata代码、示例数据、计算结果及方法说明,围绕标准化、指标占比、信息熵、权重和加权汇总介绍操作。可用于学习面板综合指标构建,并根据研究对象调整指标体系。

基本信息

数据频率年度
当前预览样本量1190 行
文件格式Stata / Stata代码 / PDF / Word
文件包大小628.02 KB
包含内容数据表2份、代码1份、文档2份
所属分类

样本年份分布

合计 1,190 行 · 17 个年份

查看年份明细
年份样本量
200170
200270
200370
200470
200570
200670
200770
200870
200970
201070
201170
201270
201370
201470
201570
201670
201770

测算方法

采用熵值法对面板数据中的各项指标客观赋权并计算综合指标。每项指标的标准化极值取自全部地区、全部年份的样本,指标比重以标准化值除以该指标在全部地区、全部年份的标准化值之和。随后计算信息熵与信息冗余度,以各指标冗余度占全部指标冗余度之和的比例确定权重,再将指标权重与标准化值相乘并加总,得到地区年度综合指标。信息熵中log(m)的m取样本年份数。

以下字段、样本量及样本仅对应当前展示的数据表,不代表资料包全部文件。查看文件结构

字段列表共 8 个字段

字段类型均值标准差最小值最大值缺失率
id整数37.6428571421.406616771740.0000%
year整数20094.901039179200120170.0000%
x1数值8.63568992135.15519487-4.8632781058.37360.0000%
x2数值27.410049015.220849833038.2916670.0000%
x3数值16.218606065.0861098074.629886133.0118870.0000%
x4数值75.2282124631.4042208215.635592189.590170.0000%
x5数值65.0187130249.762934661.385387312.026940.0000%
Score数值0.36492276140.15106289950.04312805460.94070561820.0000%

数据样本预览

资料样本(部分数据)

仅可预览前100 行、100 列,滚动查看其余行列,完整数据以下载文件为准。

idyearx1x2x3x4x5Score
1200129.77962618.7516.7637955.1910055.1993870.216736092041
1200218.67907622.33333315.77431953.7051485.36490270.322724016306
120035.733522824.66666716.53837952.2439113.90741690.0846671891126
120044.950161622.58333317.79190945.0944514.56382250.260033456067
120052.64551112216.78723750.9291155.38808990.205832620184
120060.3391631922.7513.58394762.8583445.96564020.179240413489
120074.225988322.08333314.77507558.7061638.01426430.284555320642
120081.418301922.54166715.48712261.13416512.1997920.371997684387
120094.26895421.58333314.80339462.12477211.2223250.362239325215
120103.961800322.7513.77264965.70142610.997780.340636356007
120111.382446625.45833311.45042271.27859711.929150.352847193677
120122.314524125.16666711.23157770.73001412.1170980.362990762202
120133.673827324.41666711.64349671.93812712.9901030.423336963368
120144.862990523.79166713.20671476.68452212.79580.38544518294
120155.734333424.2516.14528671.32432916.2658050.496756966997
120163.913043524.517.22675669.86666215.2082410.531937319674
120174.524211521.16666720.66746567.47227613.7155110.48381960138
220012.243366726.58333319.58965868.25660190.9051980.154017117009
220021.860973830.519.56574370.08367190.9051980.227176186762
220031.305983132.37519.60079174.8676990.9051980.0763582120477
220040.9224658432.7519.55305576.92714990.9051980.249725528262
220050.568990773219.84366778.2601492.0970340.224444731043
220062.344864632.08333319.21971785.36049690.9051980.244270544019
220072.64999923518.97616887.53666589.7133620.330742474172
220081.810359534.62518.83869786.94816888.5215260.405146029433
220091.355556735.7518.9796486.38738387.8063660.34346739306
220102.061203535.20833318.89135990.79234687.7658460.356297122576
220112.299138834.54166719.34627394.03380594.3241060.450067444754
220121.44154733.95833319.2582998.08831194.4376060.437325308315
220132.16855634.7518.744792100.7332592.9198840.492681387803
220143.215950234.45833319.272131102.0736895.8129660.428106509432
220150.5063083536.520.68421387.06223197.7395750.646625573669
220161.813536335.41666720.49254899.01979698.5283240.617634188588
220173.28658233.62519.896568105.1027996.0610990.535457240403
320012.704034824.58333320.846595152.4643243.0935730.13013208209
32002-0.4522273823.7520.23711164.1154241.6118220.177515789764
320032.43155132719.482259148.5820845.0006260.0661823507072
32004-0.366533862920.764698128.489150.0709650.210511382
32005-1.28758828.58333320.815426141.831752.3197450.178313126529
32006-0.704852953016.208927135.8090240.5117540.18846213493
32007-1.207571831.517.260399127.0261141.8156260.266197662802
32008-0.4955401431.70833317.999289130.6075244.3596180.364042885851
320091.593625531.70833317.316024128.0914942.1254550.308011501023
320102.352941231.515.438407140.7372343.9428960.289755931217
320112.586206931.16666714.056754148.3134943.6843410.327120552997
320122.007469730.83333312.712744147.1018644.8770460.300813097909
320133.256666728.512.099779137.7850553.1180540.358179849286
320143.526003228.511.069286145.8826664.2134460.298385238117
320152.795512828.513.978344117.9637371.4372670.466036390359
320161.961884728.91666712.927963120.472467.6972630.459660264968
32017-0.4014869926.95833313.872921174.1589669.552680.296131061606
4200110.297812144.629886128.20949620.8817610.131609578854
420022.37712916.8333334.727499226.07608818.9119980.176000871482
420035.305601122.0833334.902982126.32551419.9866310.0600194311726
420048.40223822.755.125679827.88006320.4966380.218462613938
420056.1066959225.039615228.3879420.9872340.181014017461
420062.208256220.4166674.973121429.32171421.7793890.144732268422
420072.0071737224.845659832.09801724.1795930.216279959037
420083.332564920.755.022648628.96738126.2081250.309231481565
420095.668707720.5833335.128298627.65788526.0386280.341524292841
420107.587536420.7916675.174383126.85823427.9134030.332577495422
420117.046618222.4583335.180225234.39693529.343830.451793911811
420126.765261222.3755.440078638.11192531.1657020.452578868089
420139.10698522.0833335.359456239.94238332.0428330.520756706254
420148.9019449225.178276942.62091434.0421920.396855740049
420155.423472423.7916675.093745240.09279636.1910380.412872616801
420168.126676423.3755.075325837.80284340.9613230.4754838109
4201711.33291520.3333335.097446747.4208542.4702410.46600318113
520011.46796726.7521.131267115.5113768.1622240.142106858298
520022.077021130.2521.504809118.0600968.1622240.221089243049
520031.628160529.58333320.955778124.3666968.1622240.0718194976327
520040.949250293120.856703123.484565.9366620.228924054342
520051.120848230.66666721.015862123.9972465.9366620.213371134063
520062.544517831.08333320.874403141.0790765.9366620.232161574975
520072.469258233.83333321.278694138.6944765.9366620.321512967055
520081.645214433.58333321.916375135.1248963.71110.407325822773
520091.58896433.522.351607131.9903162.2131250.334264157939
520102.097283133.33333322.03526136.0378361.4510760.337896008165
520112.781432632.522.107847143.3762263.3030990.407289957826
520121.791207732.521.892255147.693965.5291810.388272954059
520131.823056330.521.586598151.1636268.2267110.400494496463
520144.489444231.33333322.554389158.9080562.3465860.410055643283
52015-0.0531456732.87524.021313136.3567658.2904290.591031755683
520162.189299231.87523.554857151.1001856.4964990.591369956358
520173.532082130.523.773675162.7536754.9621570.502480530676
6200110.19320720.83333313.5726249.73798648.2018450.158307776851
6200212.42548721.513.32726749.85629152.737230.260309015604
620034.708444425.513.90352950.46966358.2754240.0723536501279
620047.67322927.7514.21887152.28116264.0518430.264635060522
620052.159516327.514.79789244.16825464.4499920.210109608357
620064.6082327.58333314.539345.59777558.7218030.234645796936
620071.589653826.29166715.7241345.22782253.55660.275984145123
620080.9282588524.7515.9678949.35026151.0016770.362654702896
620093.33727522.33333316.52114251.96783547.880520.345511747174
620104.437380822.87516.25853757.46426742.6507010.351614273149
620115.393231119.95833315.97455867.64194345.0254630.42758636477
620124.28554931914.35423374.5378537.8000930.376833263719
620138.706247218.12514.05865376.06191236.9684280.488924862691
6201414.00040819.37513.27737482.86702134.6926250.472691247344
620153.349369820.16666714.70876568.62707437.0182160.373227558323

代码公开披露

仅展示前 30 行,供了解变量构造与处理流程,完整代码请下载文件查看。

import excel "数据.xlsx", firstrow clear
save data.dta, replace


///从这开始运行
use data,clear
*=========================== 需要设置 =========================== 
//正向指标
global positive_var x1 x2 x3
//负向指标
global negative_var x4 x5
*================================================================ 


*========================= 后面无需改动 ========================= 

//所有指标
global all_var $positive_var $negative_var
//年份
qui sum year
global min_year=r(min)
global max_year=r(max)

forvalues year=$min_year / $max_year{
	use data.dta, clear
	keep if year==`year'

	//标准化数据 正向指标
	foreach i in $positive_var {
		qui sum `i'